Knowledge catalogue
arXiv:2607.13853v1 Announce Type: new Abstract: Chemical pollutants released into the environment are transported by turbulent flows, generating complex, intermittent plume structures that threaten ec
Tool: Mermaid to Unicode box art (grok-mermaid) While exploring the codebase for the newly open-sourced Grok CLI coding agent I came across xai-grok-markdown/src/mermaid.rs, a 'self-contained terminal
arXiv:2607.14072v1 Announce Type: new Abstract: Bioacoustic foundation models rely on large-scale citizen science platforms like Xeno-Canto for geographically and ecologically diverse data. Recent wor
arXiv:2607.14005v1 Announce Type: new Abstract: Driving-world generation has emerged as a core capability for scalable autonomous-driving simulation, yet existing methods remain limited in object-leve
arXiv:2607.13187v1 Announce Type: new Abstract: Face identification has achieved remarkable performance under normal conditions. Yet, its accuracy often degrades significantly when query faces are par
arXiv:2607.13688v1 Announce Type: new Abstract: Emerging sustainable materials increasingly rely on engineered hierarchy and microstructure to achieve control of their properties and mechanical behavi
arXiv:2607.13403v1 Announce Type: new Abstract: Efficient task allocation for large-scale Heterogeneous Multi-Robot Systems (HMRS) is critical, yet dealing with complex temporal logic tasks in partial
arXiv:2601.12349v3 Announce Type: replace-cross Abstract: Large multimodal model powered GUI agents are emerging as high-privilege operators on mobile platforms, entrusted to perceive screen content a
arXiv:2607.13119v1 Announce Type: cross Abstract: In standard federated learning systems, the parameter server broadcasts the global model to the participating devices in every iteration. Motivated by
arXiv:2607.13771v1 Announce Type: new Abstract: We report a search for dark matter (DM) produced in association with a leptonically decaying (Z) boson at (sqrt{s}=13) TeV using CMS Run 2015D open data
arXiv:2607.13558v1 Announce Type: new Abstract: Urban region profiling constitutes a core problem in urban computing, supporting applications such as population estimation, economic assessment, and en
arXiv:2509.10033v2 Announce Type: replace Abstract: Sparse dictionary coding represents signals as linear combinations of a few dictionary atoms. It has been applied to images, time series, graph sign
arXiv:2607.14041v1 Announce Type: cross Abstract: Historical Manchu OCR must accommodate various visually distinct writing styles, including regular script, running script, and the semi-cursive chance
arXiv:2408.10581v3 Announce Type: replace Abstract: This work introduces a novel and generalizable multi-view Hand Mesh Reconstruction (HMR) model, named POEM, designed for practical use in real-world
arXiv:2607.13415v1 Announce Type: new Abstract: Recent advances in generative models and technological innovations have significantly addressed the fundamental challenges of character image animation.
arXiv:2607.13826v1 Announce Type: cross Abstract: Accurate determination of pancreatic ductal adenocarcinoma (PDAC) resectability relies on evaluating how the tumor interacts with major peripancreatic
arXiv:2607.13984v1 Announce Type: cross Abstract: Longitudinal tumor measurements, dropout information, and genetic covariates provide complementary information about treatment response, but integrati
arXiv:2607.13978v1 Announce Type: cross Abstract: Music-driven dance generation aims to produce human motion that is both rhythmically synchronized and semantically consistent with music. While recent
arXiv:2607.13763v1 Announce Type: cross Abstract: Single-task fine-tuning of graph neural networks (GNNs) for power grid problems exhibits a systematic failure mode: models that achieve the lowest in-
arXiv:2603.16103v2 Announce Type: replace Abstract: 3D Gaussian Splat (3DGS) enables high-fidelity, real-time novel view synthesis by representing scenes with large sets of anisotropic primitives, but
arXiv:2509.24563v3 Announce Type: replace Abstract: Recent advances in video large language models (VideoLLMs) call for new evaluation protocols and benchmarks for video-language understanding. Inspir
arXiv:2607.13220v1 Announce Type: new Abstract: Most AI-for-science systems focus on scaling a single reasoning process through better models, larger context windows, long-horizon agentic execution, o
arXiv:2503.24092v2 Announce Type: replace-cross Abstract: Motivated by the rapidly growing field of mathematics for operator approximation with neural networks, we present a novel universal operator a
arXiv:2607.13563v1 Announce Type: new Abstract: Generating high-quality triangle meshes is essential for film, gaming, and interactive 3D applications. Mainstream methods rely on mesh serialization an
arXiv:2607.13837v1 Announce Type: cross Abstract: In real-world applications, node classification on graphs often faces the challenge of class imbalance, where majority classes dominate training, resu
arXiv:2607.13414v1 Announce Type: cross Abstract: Non-expansive two-time-scale stochastic approximation is governed by a slow stochastic Krasnoselskii--Mann fixed-point iteration rather than by contra
arXiv:2601.02023v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) increasingly utilize massive context windows as working memory for autonomous tasks, their reliability fluctua
arXiv:2603.14709v3 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) enhances zero-shot time series (TS) forecasting by leveraging external knowledge bases, yet existing approaches
arXiv:2505.18231v3 Announce Type: replace-cross Abstract: Large Language Model (LLM) inference is typically memory-intensive, especially when processing large batch sizes and long sequences, due to th
arXiv:2607.13704v1 Announce Type: new Abstract: The dominance of traditional rule-based methods in autonomous driving has gradually been replaced by learning-based approaches. While learning-based pla
I managed to get this model working on 2x 3090s with full 262k ctx and N=4, if anyone is interested to try it, thanks to this quant: https://huggingface.co/danielrmay/NVIDIA-Nemotron-Labs-3-Puzzle-75B
NVIDIAとSakana AI、オープンモデルによるイノベーションのため協業拡大 本日、Sakana AIはNVIDIAとのコラボレーションを強化し、日本発の「集合知」の取り組みを次なるフェーズへ進めることを発表します。 私たちのマルチエージェント・オーケストレーションシステム「Sakana Fugu」に、Nemotronファミリーを含むNVIDIAのオープンモデル群を統合します。 Sakana
arXiv:2603.08521v2 Announce Type: replace Abstract: Understanding dynamic 3D environments in a spatially continuous and temporally consistent manner is fundamental for robotics and autonomous driving.
arXiv:2502.13467v2 Announce Type: replace Abstract: The K-Max combinatorial multi-armed bandit problem arises in applications such as recommendation and distributed decision making, where the reward i
Open models are already being used in the enterprise. Over 85% of the Fortune 500 companies already use Ollama to fulfill specific tasks. @jmorgan Why open models and Ollama? Ownership. Open models ar
arXiv:2607.13078v1 Announce Type: cross Abstract: LLMs are now proposed for fraud detection, scam investigation, content moderation, and other trust-and-safety workflows. Much of the public literature
arXiv:2607.13686v1 Announce Type: new Abstract: We study the contextual combinatorial semi-bandit (CCSB) problem with general reward function approximation. At each round, the learner observes a conte
arXiv:2505.14303v3 Announce Type: replace-cross Abstract: Using Resistive Random Access Memory (RRAM) crossbars in Computing-in-Memory (CIM) architectures offers a promising solution to overcome the v
arXiv:2607.13157v1 Announce Type: new Abstract: Agent memory is a systems problem for long-horizon agents. Practical deployments require retention of task state across extended conversations, recovery
arXiv:2607.13420v1 Announce Type: new Abstract: Clicks on homepage marketing blocks are driven by a dual-mechanism of content interest and access habits. However, habitual clicks often create Pseudo-P
arXiv:2607.13037v1 Announce Type: new Abstract: When a data contributor requests removal, model trainers face a practical gap: unlearning algorithms require a forget set, yet no tool can locate which
arXiv:2607.13639v1 Announce Type: cross Abstract: We introduce OvisOCR2, a 0.8B document parsing model. OvisOCR2 is designed as an end-to-end parser: given a document page image, it generates a Markdo
arXiv:2607.13550v1 Announce Type: cross Abstract: Boosting is one of the most successful learning techniques for standard classification and regression tasks. Its extension to multi-output prediction
arXiv:2607.13312v1 Announce Type: new Abstract: This study presents and validates a minimum-lap-time planning (MLTP) framework for motorsport applications that embeds robustness against both state dis
arXiv:2607.13918v1 Announce Type: cross Abstract: Serial verification gates are a core reliability primitive in LLM harnesses: a candidate answer is returned only if k verifier calls all accept it. Un
arXiv:2603.10330v2 Announce Type: replace-cross Abstract: Autonomous driving in complex traffic requires planners that generalize beyond hand-crafted rules, motivating data-driven approaches that lear
arXiv:2607.13941v1 Announce Type: new Abstract: Video aesthetic assessment (VAA) aims to predict how aesthetically pleasing a video is, yet remains far less explored than other visual assessment tasks
arXiv:2606.15587v2 Announce Type: replace Abstract: Expert demonstrations are widely assumed to be the gold standard for robot imitation learning. Yet for fine-grained manipulation such as insertion,
arXiv:2502.16167v2 Announce Type: replace-cross Abstract: Diffusion models (DMs) have advanced text-to-image (T2I) synthesis, yet their personalization capabilities raise serious privacy and copyright
arXiv:2607.14047v1 Announce Type: new Abstract: Autonomous data collection governs the volume and quality of real-world trajectories for manipulation policy learning. Existing pipelines reduce human e
arXiv:2607.13891v1 Announce Type: cross Abstract: Multi-object detection and tracking from noisy point clouds remain challenging in many data-scarce radar applications. Current Bayesian trackers based
arXiv:2607.13928v1 Announce Type: cross Abstract: Whistleblowers are a key safeguard against organizational wrongdoing, but the threat of retaliation deters reporting. Existing whistleblower-protectio
arXiv:2607.13945v1 Announce Type: new Abstract: Imaging spectrometers increasingly distribute source-resolved methane plume products in which the plume mask, integrated mass enhancement (IME), plume l
arXiv:2602.02741v2 Announce Type: replace Abstract: Articulation modeling enables robots to learn joint parameters of articulated objects for effective manipulation which can then be used downstream f
arXiv:2601.20379v2 Announce Type: replace Abstract: Large language models (LLMs) struggle with complex, long-horizon reasoning due to instability caused by their frozen policy assumption. Current test
arXiv:2507.16849v3 Announce Type: replace-cross Abstract: We propose a vision transformer (ViT)-based deep learning framework to refine disaster-affected area segmentation from remote sensing imagery,
arXiv:2607.13058v1 Announce Type: new Abstract: As haptic interfaces integrate more seamlessly into wearables and everyday environments, they increasingly require actuators that are soft, thin, silent
arXiv:2511.13592v2 Announce Type: replace-cross Abstract: The existing method of GS-PowerOpt solves the non-convex optimization problem of the form max_{oldsymbol{x} in R^d} f(oldsymbol{x}) through ma
arXiv:2607.13466v1 Announce Type: new Abstract: Most multimodal learning methods improve how heterogeneous representations are aligned and fused, while post-fusion enhancement remains less explored. W
arXiv:2607.13051v1 Announce Type: cross Abstract: TriAttention is a recent method for shrinking the KV cache of long-reasoning LLMs: it scores each cached key by how much attention it is likely to rec